{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import random\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.random.normal(0,20,1000)\n",
    "bins = np.arange(-100, 100, 5)\n",
    "plt.hist(data, bins=bins, edgecolor='black')\n",
    "plt.xlim([min(data)-5, max(data)+5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x=np.random.rand(10), y=np.random.rand(10))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
